Exploring the link between wealth and happiness

Does an individual's happiness hinge upon their income, or are there other factors at play?

Grades 5 - 9

This week, we examine the factors that influence happiness levels across different countries.

To answer our question we:

Used data from the World Happiness Report.

Visualizing the data

First, we arranged the countries by continent, ranking them based on surveyed levels of happiness. In this plot, the term “ladder score” is synonymous with “happiness score”:

At first glance, the visualization suggests that people in Europe are, on average, happier, while people from Asian countries report being less happy.

Continuing our exploration, we created a colour-coded map reflecting the happiness score of each country. On this map, the colour of each country corresponds to its happiness score. The scores range from 0 to 10, with 0 meaning the 'worst possible life for you' and 10 being 'the best possible life for you.’

Finland claims the highest happiness score among all countries, followed closely by Denmark and Iceland.

• What do you notice about the map below?

Our data source defines and measures various factors that contribute to happiness:

• Gross domestic product or GDP (measured in $), which measures the total monetary value of all goods and services produced by a country during a specific time frame
• Life expectancy (measured in years)
• Social support (measured as the national average of the binary responses to the question: "If you were in trouble, do you have relatives or friends you can count on to help you whenever you need them, or not?")
• Freedom (measured as the national average of the binary responses to the question "Are you satisfied or dissatisfied with your freedom to choose what you do with your life?”)
• Generosity (measured by how many people in a country donate money to charity, taking into account their income level. It is plotted as the average response to the question: "Have you donated money to a charity in the past month?")
• Corruption (measured as the national average of the binary responses to two questions: “Is corruption widespread throughout the government or not,” and “Is corruption widespread within businesses or not?")

Based on the line graphs, it appears that factors such as gross domestic product, social support, and healthy life expectancy contribute more towards happiness scores in a country.

• Based on the visualizations above, what conclusions can you draw about world happiness?

Reflect on what you see

Look and interact with the data visualizations above. When you hover your mouse over the plots, you’ll notice more information appears. You can also use the legend to make plots appear and disappear.

Think about the following questions.

• What do you notice about the line graphs?
• What do you wonder about the data?

Use the fill-in-the-blank prompts to summarize your thoughts.

• “I used to think _______”
• “Now I think _______”
• “I wish I knew more about _______”
• “These data visualizations remind me of _______”
• "I really like _______”

Learn how we visualized the data

Go to our walk-through (in Jupyter notebook format) to see how the data science process was applied to create these graphs, from formulating a question to gathering the data and analyzing the data with code.